Results 31 to 40 of about 547 (178)
A Two-Stage Network for Image Deblurring
IEEE Access, 2021 Blind deblurring is a typical challenge in image processing, carried out to correct various complex types of distortions that occur in the real world. Although learning-based deblurring methods have substantially outperformed the traditional algorithms ...
Ze Pan, Qunbo Lv, Zheng Tan
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A Blur Restoration Algorithm Based on L0 Regularization [PDF]
Jisuanji gongcheng, 2016 Aiming at the motion blur,a new blind deblurring algorithm is proposed,which is based on the L0 regularization restraints and the prior knowledge of natural image gradient distribution to obtain the real motion kernel.In the proposed methods,T-smooth ...
FANG Shuai,FAN Dong,YU Lei,CAO Fengyun
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A Motion Deblur Method Based on Multi-Scale High Frequency Residual Image Learning
IEEE Access, 2020 Non-uniform blind deblurring of dynamic scenes has always been a challenging problem in image processing because of the diverse of blurring sources. Traditional methods based on energy minimization cannot make accurate kernel estimation. It leads to that
Keng-Hao Liu +3 more
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Solar Speckle Image Deblurring With Deep Prior Constraint Based on Regularization
IEEE Access, 2022 The solar speckle image has the characteristics with single features, more noise, and blurred local details. Most of the existing deep learning deblurring methods for solar speckle images have some problems, such as high-frequency loss, artifact ...
Yahui Jin +5 more
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Blind Image Deblurring via Local Maximum Difference Prior
IEEE Access, 2020 Blind image deblurring is a well-known conundrum in the digital image processing field. To get a solid and pleasing deblurred result, reasonable statistical prior of the true image and the blur kernel is required.
Jing Liu +4 more
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Blind Image Deblurring via a Novel Sparse Channel Prior
Mathematics, 2022 Blind image deblurring (BID) is a long-standing challenging problem in low-level image processing. To achieve visually pleasing results, it is of utmost importance to select good image priors. In this work, we develop the ratio of the dark channel prior (
Dayi Yang, Xiaojun Wu, Hefeng Yin
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Blind Image Deblurring Based on Local Edges Selection
Applied Sciences, 2019 The edges of images are less sparse when images become blurred. Selecting effective image edges is a vital step in image deblurring, which can help us to build image deblurring models more accurately.
Yue Han, Jiangming Kan
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Collaborative Blind Image Deblurring
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)Blurry images usually exhibit similar blur at various locations across the image domain, a property barely captured in nowadays blind deblurring neural networks. We show that when extracting patches of similar underlying blur is possible, jointly processing the stack of patches yields superior accuracy than handling them separately.
Eboli, Thomas +2 more
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Blind and Non-Blind Deconvolution-Based Image Deblurring Techniques for Blurred and Noisy Image
Tikrit Journal of Engineering Sciences: Image deblurring is a common issue in low-level computer vision aiming to restore a clear image from a blurred input image. Deep learning innovations have significantly advanced the solution to this issue, and numerous deblurring networks have been ...
Shayma Wail Nourildean
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International Endodontic Journal, EarlyView.ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi +6 more
wiley +1 more source